Filter circuits are well known, and various different configurations are known which provide different frequency responses. Generally, a filter circuit can be categorised as any of a low-pass by which low frequency signals are passed, high-pass by which high frequency signals are passed, band-pass by which only signals within a certain frequency band are passed, or band-stop by which only signal frequencies outside a particular band are passed. Furthermore, within these classifications various other classifications can be made dependent upon the precise filter response, for example Butterworth, Chebyshev, Bessel, or the like. Such filters may be passive filters, which means that the components have no amplifying/active (either voltage or current) elements therein, or active filters, which usually comprise one or more transistors provided with a power supply to act as an active element. Various different transistor circuits are known in the art, one of which is the source follower circuit (equivalent to an emitter follower, or common collector circuit when using bipolar junction transistors). The source follower is a known basic building block for micro electronics designs, and exhibits excellent linearity. Due to this high linearity it has been proposed previously that the source follower circuit can be the basis of a high-linearity and low-power analogue filter.
Power consumption is an important factor to be considered when designing filter circuits. U.S. Pat. No. 8,710,921 discloses an example of a power-efficient and stable higher order low-pass filter. However, designing band-pass filters is typically more complex and there is currently a need for band-pass filters which have a very low power consumption, yet are stable and have a simple design.
Band-pass filters are used in various systems and fields. One such field, which is currently widely investigated, is artificial or silicon cochlea. Because human brains can process information more efficiently both in terms of power and latency even under uncontrolled conditions, increasing academic and industrial players are investigating brain-like event-driven computing methods in an attempt to mimick the brain's capability. Artificial spiking sensors such as silicon retinas and cochleas naturally provide asynchronous event-driven outputs in response to changes in the environment and are therefore a source of sensory input to processors like silicon neural networks for real-time event-driven intelligent processing. The silicon cochlea, in particular, sees wide applications in auditory sensing applications such as mobile speech control and ambient assisted living, where chip power is the major concern. To directly utilise the energy harvested from environment for powering the chip, a low power supply is also preferred.
FIG. 1 is a simplified block diagram illustrating an example of a prior art silicon cochlea system 1. In this example the on-chip silicon cochlea comprises a core 2 powered by a power source (not shown), in this example a voltage source of 0.5 V, and a 1.8 V address event representation (AER) circuitry 3, which is a protocol for asynchronously sending generated spikes off-chip. The core further comprises binaural parallel channels 5, in this example 64 channels, and a current bias generator (CBG) 7 to provide 64 geometrically scaled currents to the corresponding channels, so that the characteristic central frequencies of the channels are geometrically scaled from 20 Hz to 20 kHz, covering the frequency range of human hearing. It is to be noted that in some cases optional gain amplifiers 9 could be included on-chip. In one channel, as shown in FIG. 2, there are left and right sub-channels receiving the audio signals from left and right microphones 10 but in general, the input signals to the sub-channels could come from other sources such as antennas or electrodes. A translinear loop (TLL) 11 is provided for quality factor (Q factor) tuning of bandpass filters. The TLL 11 is shared by the left and right sub-channels. The TLL 11, having a channel biasing functionality integrated with it, distributes all the current biases needed for the circuit blocks in one channel, which include two band-pass filters (BPFs) 13, two asynchronous delta modulators (ADMs) 15 used for analogue-to-spike conversion, and two asynchronous logic (AL) units 17, which generate control signals for the ADMs and communicate with the peripheral AER circuits. The generated spikes from all the channels are transmitted off-chip by the 1.8 V AER circuitry 3. Before the BPFs, there are programmable attenuators (PAs) 19 for attenuating large input signals.
The existing methods of building analogue band-pass filters e.g. in artificial cochlea systems are: active resistor-capacitor (active RC) filters, filters using operational transconductance amplifiers (OTAs) and more specifically OTA-capacitor (OTA-C), switched-capacitor, N-path and source-follower-based filters. The switched-capacitor and N-path filter types are not suitable in the case of a band-pass filter bank (as used e.g. in artificial cochlea systems) because the central frequency is dependent on the clock frequency, which is difficult to scale with a very small scaling ratio. The active RC type is also not suitable because, for a low central frequency (in the range of kHz and below), very large and thus area-consuming resistors and capacitors are required. The source-follower-based low-pass filter has been proven to be more power-efficient than the OTA-C low-pass filter, and therefore the source-follower-based topology has been chosen to construct the BPFs used in ultra-low-power silicon cochlea systems. Currently known source-follower-based BPFs have some limitations, as explained below. For example, some BPFs have a large pass-band gain loss when two or more same unit building blocks are cascaded for high-order filters. Some other BPFs have a band-pass transfer function which is highly sensitive to input common-mode voltage, while yet other BPFs are incapable of achieving high Q values, i.e. quality factors larger than 0.5. Furthermore, currently known cochlea systems have relatively high power consumption.
There is thus a need for a BPF that can be used in artificial cochlea systems for example and which does not have the drawbacks mentioned above.